In this special guest feature, Rob Farber from TechEnablement writes that the Intel Scalable Systems Framework is pushing the boundaries of Machine Learning performance. “machine learning and other data-intensive HPC workloads cannot scale unless the storage filesystem can scale to meet the increased demands for data.”
Nimbix, a leading HPC cloud platform provider, announced a significant increase in their presence in the machine learning market space as more customers are using their JARVICE platform to help address the need for an easier, more cost efficient way of working with machine learning.
Intel Enterprise Edition for Lustre* Software has taken a leap toward greater enterprise capabilities and improved features for HPC with release of version 3.0. This latest version includes new security enhancements, dynamic LNET configuration support, ZFS snapshots, and other features asked for by the HPC community inside and outside the enterprise. Additionally, it adds the Intel Omni-Path Architecture drivers.
Deloitte Advisory Cyber Risk Services and Cray Offer Advanced Cyber Reconnaissance and Analytics Services
Deloitte Advisory Cyber Risk Services and Cray Inc. (Nasdaq: CRAY), the global supercomputing leader, introduced today the first commercially available high-speed, supercomputing threat analytics service, Cyber Reconnaissance and Analytics.
The latest addition to the NVIDIA Tesla Accelerated Computing Platform, the Tesla P100 enables a new class of servers that can deliver the performance of hundreds of CPU server nodes. Today’s data centers — vast network infrastructures with numerous interconnected commodity CPU servers — process large numbers of transactional workloads, such as web services.
In this new insideBIGDATA Guide to Scientific Research, the goal is to provide a road map for scientific researchers wishing to capitalize on the rapid growth of big data technology for collecting, transforming, analyzing, and visualizing large scientific data sets.
Converging High Performance Computing (HPC) and Lustre* parallel file systems with Hadoop’s MapReduce for Big Data analytics can eliminate the need for Hadoop’s infrastructure and speeding up the entire analysis. Convergence is a solution of interest for companies with HPC already in their infrastructure, such as the financial services Industry and other industries adopting high performance data analytics.
A number of industries rely on high-performance computing (HPC) clusters to process massive amounts of data. As these same organizations explore the value of Big Data analytics based on Hadoop, they are realizing the value of converging Hadoop and HPC onto the same cluster rather than scaling out an entirely new Hadoop infrastructure.
Building out a Hadoop cluster with massive amounts of local storage is a considerably extensive and expensive undertaking, especially when the data already resides in a POSIX compliant Lustre file system. Now companies can adopt analytics written for Hadoop and run them on their HPC clusters.
Nimbix and Mangstor announced a joint technology offering designed to accelerate high performance data analysis for seismic processing, bioinformatics, and other big data analytics use cases in the Nimbix Cloud.